Combining fold recognition and exploratory data analysis for
searching for glycosyltransferases in the genome of
Mycobacterium tuberculosis

J 2003

Combining fold recognition and exploratory data analysis for searching for glycosyltransferases in the genome of Mycobacterium tuberculosis

WIMMEROVÁ, Michaela, Soren B. ENGELSEN, Emmanuel BETTLER, Christelle BRETON, Anne IMBERTY et. al.

Basic information

Original name

Combining fold recognition and exploratory data analysis for searching for glycosyltransferases in the genome of Mycobacterium tuberculosis

Authors

WIMMEROVÁ, Michaela (203 Czech Republic, guarantor), Soren B. ENGELSEN (208 Denmark), Emmanuel BETTLER (250 France), Christelle BRETON (250 France) and Anne IMBERTY (250 France)

Edition

Biochimie, Elsevier, 2003, 0300-9084

Other information

Language

English

Type of outcome

Článek v odborném periodiku

Field of Study

10600 1.6 Biological sciences

Country of publisher

Netherlands

Confidentiality degree

není předmětem státního či obchodního tajemství

Impact factor

Impact factor: 3.707

RIV identification code

RIV/00216224:14310/03:00008870

Organization unit

Faculty of Science

UT WoS

000185771000009

Keywords in English

Glycosyltransferase; Mycobacterium; Fold recognition; Chemometrics

Abstract

V originále

Fold recognition was applied to the systematic analysis of the all sequences encoded by the genome of Mycobacterium tuberculosis H37Rv in order to identify new putative glycosyltransferases. The search was conducted against a library composed of all known crystal structures of glycosyltransferases and some related proteins. A clear relationship appeared between some sequences and some folds. It appears necessary to complete the fold recognition approach with a statistical approach in order to identify the relevant data above the background noise. Exploratory data analysis was carried out using several methods. Analytical methods confirmed the validity of the approach, while predictive methods, although very preliminary in the present case, allowed for identifying a number of sequences of interest that should be further investigated. This new approach combining bioinformatics and chemometrics appears to be a powerful tool for analysis of newly sequenced genomes. Its application to glycobiology is of great interest.

Links

LN00A016, research and development project

Name: BIOMOLEKULÁRNÍ CENTRUM

Investor: Ministry of Education, Youth and Sports of the CR, Biomolecular Center

Citovat

WIMMEROVÁ, Michaela, Soren B. ENGELSEN, Emmanuel BETTLER, Christelle BRETON and Anne IMBERTY. Combining fold recognition and exploratory data analysis for searching for glycosyltransferases in the genome of Mycobacterium tuberculosis. Biochimie. Elsevier, 2003, vol. 85, No 7, p. 691-700. ISSN 0300-9084.

@article{488310,
   author = {Wimmerová, Michaela and Engelsen, Soren B. and Bettler, Emmanuel and Breton, Christelle and Imberty, Anne},
   article_number = {7},
   keywords = {Glycosyltransferase; Mycobacterium; Fold recognition; Chemometrics},
   language = {eng},
   issn = {0300-9084},
   journal = {Biochimie},
   title = {Combining fold recognition and exploratory data analysis for searching for glycosyltransferases in the genome of Mycobacterium tuberculosis},
   volume = {85},
   year = {2003}
}

TY  - JOUR
ID  - 488310
AU  - Wimmerová, Michaela - Engelsen, Soren B. - Bettler, Emmanuel - Breton, Christelle - Imberty, Anne
PY  - 2003
TI  - Combining fold recognition and exploratory data analysis for searching for glycosyltransferases in the genome of Mycobacterium tuberculosis
JF  - Biochimie
VL  - 85
IS  - 7
SP  - 691-700
EP  - 691-700
PB  - Elsevier
SN  - 03009084
KW  - Glycosyltransferase
KW  - Mycobacterium
KW  - Fold recognition
KW  - Chemometrics
N2  - Fold recognition was applied to the systematic analysis of the all sequences encoded by the genome of Mycobacterium tuberculosis H37Rv in order to identify new putative glycosyltransferases. The search was conducted against a library composed of all known crystal structures of glycosyltransferases and some related proteins. A clear relationship appeared between some sequences and some folds. It appears necessary to complete the fold recognition approach with a statistical approach in order to identify the relevant data above the background noise. Exploratory data analysis was carried out using several methods. Analytical methods confirmed the validity of the approach, while predictive methods, although very preliminary in the present case, allowed for identifying a number of sequences of interest that should be further investigated. This new approach combining bioinformatics and chemometrics appears to be a powerful tool for analysis of newly sequenced genomes. Its application to glycobiology is of great interest.
ER  -

WIMMEROVÁ, Michaela, Soren B. ENGELSEN, Emmanuel BETTLER, Christelle BRETON and Anne IMBERTY. Combining fold recognition and exploratory data analysis for searching for glycosyltransferases in the genome of Mycobacterium tuberculosis. \textit{Biochimie}. Elsevier, 2003, vol.~85, No~7, p.~691-700. ISSN~0300-9084.

Detailed Information on Publication Record